Advances in kernel methods support vector learning
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| Format: | Elektronisch E-Book |
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| Sprache: | English |
| Veröffentlicht: |
Cambridge, Mass.
MIT Press
©1999
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| Online-Zugang: | Volltext |
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| Beschreibung: | Includes bibliographical references (pages 353-371) and index Preface -- Introduction to support vector learning -- Roadmap -- Three remarks on the support vector method of function estimation / Valdimir Vapnik -- Generalization performance of support vector machines and other pattern classifiers / Peter Bartlett and John Shawe-Taylor -- Bayesian voting schemes and large margin classifiers / Nello Cristianini and John Shawe-Taylor -- Support vector machines, reproducing kernal Hilbert spaces, and randomized GACV / Grace Wahba -- Geometry and invariance in kernel based methods / Christopher J.C. Burgess -- On the annealed VC entropy for margin classifiers : a statistical mechanics study / Manfred Opper -- Entropy numbers, operators and support vector kernels / Robert C. Williamson, Alex J. Smola and Berhard Schölkopf -- Solving the quadratic programming problem arising in support vector classification / Linda Kaufman -- Making large-scale support vector machine learning practical / Thorsten Joachims -- Fast training of support vector machines using sequential minimal optimization / John C. Platt -- Support vector machines for dynamic reconstruction of a chaotic system / David Mattera and Simon Haykin -- Using support vector machines for time series prediction / Klaus-Robert Müller . [and others] -- Pairwise classification and support vector machines / Ulrich Kressel -- Reducing the run-time complexity in support vector machines / Edgar E. Osuna and Federico Girosi -- Support vector regression with ANOVA decomposition kernels / Mark O. Stitson . [and others] -- Support vector density estimation / Jason Weston . [et al.] -- Combining support vector and mathematical programming methods for classification / Kristin P. Bennett -- Kernel principal component analysis / Berhard Schölkopf, Alex J. Smola and Klaus-Robert Müller |
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| Beschreibung: | 1 Online-Ressource (vii, 376 pages) |
| ISBN: | 0585128294 9780585128290 0262194163 9780262194167 |